Performance measurement in flow lines – Key to performance improvement

Stricker, Nicole; Pfeiffer, András; Moser, Emanuel; Kádár, Botond; Lanza, Gisela

doi:10.1016/j.cirp.2016.04.031

Cited by 14 publications

(2 citation statements)

References 8 publications

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“…In make-to-stock manufacturing, productivity can be defined by the rate at which units flow through a system (Colledani et al 2014;Ellis et al 2010;Stricker et al 2016) -its throughput rate. Improving the flow through a manufacturing system requires the identification and reduction of bottlenecks, process variation and non-value-adding activities (Schmenner 2012).…”

Section: Process Productivitymentioning

confidence: 99%

Using process mining to improve productivity in make-to-stock manufacturing

Lorenz

Senoner

Sihn

et al. 2021

International Journal of Production Research

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This paper proposes a data-driven procedure to improve productivity in make-to-stock manufacturing. By leveraging recent developments in information systems research, the paper addresses manufacturing systems with high process complexity and variety. Specifically, the proposed procedure draws upon process mining to dynamically map and analyse manufacturing processes in an automated manner. This way, manufacturers can leverage data to overcome the limitations of existing process mapping methods, which only provide static snapshots of process flows. By bridging data and process science, process mining can exploit hitherto untapped potential for productivity improvement. The proposed procedure is empirically validated at a leading manufacturer of sanitary products. The field test leads to three concrete improvement suggestions for the company. This research contributes to the literature on production research by demonstrating a novel use of process mining in manufacturing and by guiding practitioners in its implementation.

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Section: Process Productivitymentioning

confidence: 99%

Using process mining to improve productivity in make-to-stock manufacturing

Lorenz

Senoner

Sihn

et al. 2021

International Journal of Production Research

View full text Add to dashboard Cite

show abstract

“…El valor agregado se crea una vez que se toman las acciones adecuadas en respuesta a la desviación detectada. Un conjunto óptimo de KPI debe ser mínimo, pero aun así reflejar el comportamiento del sistema (Stricker & Pfeiffer, 2016). Si existiera una desviación en el cumplimiento de los objetivos, es posible la toma de decisiones, al conocer los factores principales por los cuales no se logran las metas establecidas generando la necesidad para la creación de nuevas estrategias.…”

Section: Introductionunclassified

Indicadores clave de desempeño: Shoplogix en el proceso de corte de película flexible como herramienta para la mejora de la eficiencia

Romero

Martínez-Martínez²,

Urbano

2022

ESCS

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La industria del empaque flexible, como muchas empresas, busca continuamente mejoras que le permitan adoptarse a las condiciones del mercado y así lograr mayor competitividad. Logrando rápida respuesta al cliente dado la alta demanda, permitiendo conseguir fabricar mejores empaques, que cubran los requerimientos del mercado de alimentos. El propósito de este artículo es analizar; que son los indicadores clave de desempeño (KPI´s) el efecto y la relación en los niveles de eficiencia, en base al análisis del proceso de corte de una empresa de este sector. Se estudia la importancia y se definen los indicadores de desempeño como una forma de alcanzar los objetivos planteados por la dirección, que permita la toma de decisiones ajustándose a los cambios. Se analiza la plataforma tecnológica; Shoplogix, como una herramienta para el monitoreo y seguimiento del proceso de corte de película flexible, buscando lograr alta productividad.

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Graph-based prediction of missing KPIs through optimization and random forests for KPI systems

May

Fang

Eitel

et al. 2022

Prod. Eng. Res. Devel.

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Key performance indicators (KPIs) are widely used to monitor and control the production in industry. On an aggregated level, often represented as graphs or interrelated KPI systems, a comprehensive overview is given. However, missing or inaccurate sensor data and KPIs, as well inconsistencies in KPI based management are a major hurdle disturbing operations. To counter the impact of such missing KPIs, we propose a value optimization based approach to reconstruct the values of missing KPIs within a KPI system. While the approach shows successful reconstruction in the case study, the value optimization can be sped up through a random forest prediction of the initial optimization set. Thus, the inclusion of previous knowledge about the system behavior proves beneficial and superior to the pure optimization based approach, as validated by both randomized and simulation-based measurement data.

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Performance measurement in flow lines – Key to performance improvement

Cited by 14 publications

References 8 publications

Using process mining to improve productivity in make-to-stock manufacturing

Using process mining to improve productivity in make-to-stock manufacturing

Indicadores clave de desempeño: Shoplogix en el proceso de corte de película flexible como herramienta para la mejora de la eficiencia

Graph-based prediction of missing KPIs through optimization and random forests for KPI systems

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